Poolside

@poolsideai

We build models for agentic coding and long-horizon tasks. Try Laguna: poolside.ai/get-started

San Francisco, CA

discord.gg/poolsideai

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Poolside
@poolsideai
Jul 28
Today, we’re releasing Poolside Desktop Assistant. One place to run coding agents across macOS, VS Code, and Visual Studio. We built it for ourselves and have used it every day for the past year. Now we’re opening it up to everyone.
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Poolside
@poolsideai
Aug 17
We’ll be at ModCon ’26 in SF on August 18! @varunrandery is joining the frontier models panel to talk about building models for long-horizon agentic work, where open models differentiate, and what it takes to get them into production. Join us in SF or tune in online ↓
Modular
@Modular
Aug 13
Building frontier models involves a hundred decisions rarely discussed publicly: when to stop scaling, what data to keep, how to differentiate, whether to release the weights. On August 18th at ModCon '26, Paige Bailey of @GoogleDeepMind, Joseph Spisak of @reflection_ai, Victor
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Poolside
@poolsideai
Aug 17
Agentic evals are messy. A benchmark score tells you something about model performance, but it also reflects the whole system around it: the harness, sandbox, dependencies, timeouts and sometimes a loophole the agent found in the task. That’s why trajectories matter so much to
Arena.ai
@arena
Aug 14
Meet… Arena Conversations. @petergostev sits down with @poolsideai researchers,Connor Adams and Aalhad Patankar, to discuss how they’re building frontier open coding models. Episode drops today at 10am PT on our YouTube. They dig into Poolside's Laguna model family, why the
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Poolside
@poolsideai
Aug 12
Come hear @mgalle and @sudip_r0y get into the weeds on post-training, agent RL, continuous learning, and what it takes to make models work reliably in production!
adaption
@adaption_ai
Aug 12
First episode of Field Notes, our new monthly series on the leaders shaping AI. @sudip_r0y, Adaption Co-founder, and @mgalle, post-training lead at @poolsideai discuss the last 5% of reliability and what it actually costs.
Poolside
@poolsideai
Aug 11
we knew the community could make Laguna faster. 2.6x faster is pretty fun :) huge congrats to the winner, and to all 35 solvers who spent the last few weeks pushing Laguna XS 2.1 further! more reasons to build in the open, together 🤝
Eigen Labs
@eigenlabs
Aug 11
We started the MLX.fast challenge with @poolsideai with one key question. How much faster can the community make Laguna XS 2.1 run on a Mac? The answer so far has been 2.6x faster. Nearly 1,800 submissions and 35 solvers later, the challenge comes to a close
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